LIDAR systems employ pulses of light to measure distance to an object based on the time of flight (TOF) of each pulse of light. A pulse of light emitted from a light source of a LIDAR system interacts with a distal object. A portion of the light reflects from the object and returns to a detector of the LIDAR system. Based on the time elapsed between emission of the pulse of light and detection of the returned pulse of light, a distance is estimated. In some examples, pulses of light are generated by a laser emitter. The light pulses are focused through a lens or lens assembly. The time it takes for a pulse of laser light to return to a detector mounted near the emitter is measured. A distance is derived from the time measurement with high accuracy.
Some LIDAR systems employ a single laser emitter/detector combination combined with a rotating mirror to effectively scan across a plane. Distance measurements performed by such a system are effectively two dimensional (i.e., planar), and the captured distance points are rendered as a 2-D (i.e. single plane) point cloud. In some examples, rotating mirrors are rotated at very fast speeds (e.g., thousands of revolutions per minute).
In many operational scenarios, a 3-D point cloud is required. A number of schemes have been employed to interrogate the surrounding environment in three dimensions. In some examples, a 2-D instrument is actuated up and down and/or back and forth, often on a gimbal. This is commonly known within the art as “winking” or “nodding” the sensor. Thus, a single beam LIDAR unit can be employed to capture an entire 3-D array of distance points, albeit one point at a time. In a related example, a prism is employed to “divide” the laser pulse into multiple layers, each having a slightly different vertical angle. This simulates the nodding effect described above, but without actuation of the sensor itself.
In all the above examples, the light path of a single laser emitter/detector combination is somehow altered to achieve a broader field of view than a single sensor. The number of pixels such devices can generate per unit time is inherently limited due limitations on the pulse repetition rate of a single laser. Any alteration of the beam path, whether it is by mirror, prism, or actuation of the device that achieves a larger coverage area comes at a cost of decreased point cloud density.
As noted above, 3-D point cloud systems exist in several configurations. However, in many applications it is necessary to see over a broad field of view. For example, in an autonomous vehicle application, the vertical field of view should extend down as close as possible to see the ground in front of the vehicle. In addition, the vertical field of view should extend above the horizon, in the event the car enters a dip in the road. In addition, it is necessary to have a minimum of delay between the actions happening in the real world and the imaging of those actions. In some examples, it is desirable to provide a complete image update at least five times per second. To address these requirements, a 3-D LIDAR system has been developed that includes an array of multiple laser emitters and detectors. This system is described in U.S. Pat. No. 7,969,558 issued on Jun. 28, 2011, the subject matter of which is incorporated herein by reference in its entirety.
In many applications, a sequence of pulses is emitted. The direction of each pulse is sequentially varied in rapid succession. In these examples, a distance measurement associated with each individual pulse can be considered a pixel, and a collection of pixels emitted and captured in rapid succession (i.e., “point cloud”) can be rendered as an image or analyzed for other reasons (e.g., detecting obstacles). In some examples, viewing software is employed to render the resulting point clouds as images that appear three dimensional to a user. Different schemes can be used to depict the distance measurements as 3-D images that appear as if they were captured by a live action camera.
Existing LIDAR systems employ a beam of light to interrogate a particular volume of the surrounding environment at any given time. The detection of return signals includes significant sources of measurement noise that are exacerbated as measurement ranges are extended. In many applications, the signal to noise ratio of measured signals is improved by increasing laser pulse intensity.
In addition, imaging resolution depends on the density of the 3-D “point cloud” generated by the LIDAR system. Oftentimes, to improve imaging resolution, the density of the 3-D “point cloud” is increased by increasing the rate of pulse emission and capture of corresponding return signals.
Increases in pulse rate, pulse intensity, or both, require increases in light emission, and consequent increases in energy consumption and heat generation due to energy losses associated with the light source and power electronics. In particular, the additional heat generation is undesirable, particularly as the size of 3-D LIDAR systems continue to shrink.
Improvements in power management of LIDAR systems are desired, while maintaining high levels of imaging resolution and range.